JP7359401B2 - Extraction device and extraction method - Google Patents

Description

The present invention relates to an extraction device and an extraction method for extracting data.

Patent Document 1 discloses a team generation support device that supports team generation while taking human relationships among workers into consideration. In this team generation support device, the work template database stores target task information for performing the work, and the CPU generates team candidates for workers to perform the work based on skill information set in the worker skill database. , obtains and provides evaluation values for past work performance for each team candidate from the work performance database, obtains evaluation values between workers from the mutual evaluation database, calculates the degree of relevance, and provides each team candidate. .

Japanese Patent Application Publication No. 2001-282965

However, the team generation support device of Patent Document 1 does not take into consideration the cases where there are workers who cannot participate in the work, workers who refuse to participate in the work, and workers who do not express their intention to participate in the work. If it exists, team candidates cannot be generated.

The present invention aims to extract groups suitable for event activities.

An extraction device that is one aspect of the invention disclosed in this application is an extraction device that has a processor that executes a program, a storage device that stores the program, and a communication interface that can communicate with a plurality of terminals, Each user of the terminal can access a database that stores the skills possessed by the user, experience points indicating the degree of mastery of the skills, and the group to which the user belongs, and the processor a first communication process in which an event request requesting the event is received from each of the terminals, and after the first communication process, a question regarding the event is received from each of the terminals; A second communication process of transmitting a message to the client's terminal; and after the second communication process, receiving an answer to the question from the client's terminal, and inputting the answer information, which is requested for each skill. By inputting the answer sentence into a learning model that outputs the experience value required for each skill, required skill information indicating the experience value required for the event is generated for each skill, and for each group, the A generation process that generates skill information for each group by calculating statistical values of experience values of each skill of the users in the group, and from among the skill information for each group generated by the generation process, As a result of an extraction process for extracting a specific group that satisfies the requested skill information, and a request to participate in the event being sent to a terminal of a specific user who belongs to the specific group extracted by the extraction process, an update process that updates specific skill information possessed by the specific group based on a response from a specific user's terminal; and the specific skill information updated by the update process satisfies the requested skill information. The present invention is characterized in that it executes a determination process for determining whether or not the above determination process is performed, and a transmission process for transmitting the determination result of the determination process to the client 's terminal.

According to a typical embodiment of the present invention, it is possible to extract a group appropriate for the activity of an event. Problems, configurations, and effects other than those described above will become clear from the description of the following examples.

FIG. 1 is an explanatory diagram showing an example of matching with a request from a client. FIG. 2 is an explanatory diagram showing an example of the system configuration of the matching system. FIG. 3 is a block diagram showing an example of the hardware configuration of a computer (server, terminal). FIG. 4 is an explanatory diagram showing an example of the storage contents of the user DB. FIG. 5 is an explanatory diagram showing an example of the contents stored in the skill DB. FIG. 6 is a sequence diagram showing an example of a matching sequence by the matching system. FIG. 7 is an explanatory diagram showing an example of a request input screen. FIG. 8 is an explanatory diagram showing an example of entering the answer input screen. FIG. 9 is an explanatory diagram showing an example of the required skill information display screen. FIG. 10 is an explanatory diagram showing the extraction results of the group extraction process (step S603). FIG. 11 is an explanatory diagram showing an example of a participation request screen. FIG. 12 is an explanatory diagram showing an example of the answer screen. FIG. 13 is a flowchart showing a detailed processing procedure example of the group extraction process (step S603) shown in FIG. FIG. 14 is a flowchart showing a detailed example of the processing procedure of the participating member determination process (step S604) shown in FIG. FIG. 15 is an explanatory diagram showing an example of determining whether or not the required experience value can be satisfied in step S1404. FIG. 16 is a flowchart illustrating a detailed processing procedure example of the missing skill replenishment process (step S1406). FIG. 17 is an explanatory diagram showing an example of a user search in step S1602. FIG. 18 is a flowchart illustrating a detailed processing procedure example of post-processing. FIG. 19 is an explanatory diagram showing an example of an update result screen. FIG. 20 is an explanatory diagram showing an example of a supplementary member selection screen. FIG. 21 is an explanatory diagram showing an example of the supplementary member selection screen when checking the checkbox.

In the future of Japanese society, there is a high possibility that the life that was normally enjoyed as a matter of course with generous services will suddenly become unsustainable due to the arrival of an unprecedented series of disasters and the disparity between rural and urban areas. In doing so, what is needed is to first have food, clothing, and shelter, as the saying goes, ``Once you have enough food, clothing, and shelter, you will know manners.'' To do this, they need to be able to acquire the basic skills of producing their own food, clothing, and shelter as part of their survival skills, and they need a place to learn these skills together with a group.

Specifically, for example, acquiring practical skills such as cultivating fields, harvesting, and processing crops by oneself, as well as making clothing and housing from the minimum necessary materials is an unpredictable and unpredictable process. It is thought to be the key to recovering as quickly as possible in the event of a natural disaster.

Below, a server that can access a database (DB) that registers information on people with such skills will search for groups that have the skills to fulfill requests from clients who are in trouble due to disasters or rural-urban disparities. . This makes it possible to respond to the requester's request based on the searched group.

<Matching example>
FIG. 1 is an explanatory diagram showing an example of matching with a request from a client. In this example, the event requested by the client 101 is, for example, "repair of the roof of one's home." When the server 100 receives an event request from the client 101, the server 100 calculates the skill required for the event (required skill) and its experience value (required experience value), and outputs it as required skill information 110. For example, there are 10 types of skills (physical ability, general life, medicine/pharmacy, agriculture, civil engineering and architecture, mechanical engineering, electrical engineering, information engineering, language ability, and law). Experience points indicate the degree to which a skill has been acquired. In this embodiment, these 10 types of skills and skill information representing their experience values are expressed in a skill chart.

The server 100 is an extraction device that extracts groups that match the required skill information 110. A group is a collection of users 102 who belong to an organization such as a company, university, or NPO (Nonprofit Organization), or an organization that spans organizations, such as a circle, seminar, or friends connected within an SNS (Social Networking Service). This is a set of users 102 who belong to a community that does not belong to the community. Note that the users 102 who belong to a group are sometimes referred to as members 102.

In FIG. 1, as an example, the server 100 stores skill information 111 that is the skills and experience values of group G1, skill information 112 that is the skills and experience values of group G2, and requested skill information 110. Search for satisfying skill information. The experience value of each skill in the skill information 111 and 112 is a statistical value selected from the maximum value, average value, or median value of the experience values of the members belonging to the groups G1 and G2, respectively.

Then, for example, if the server 100 determines that the skill information of the group G1 is superior among the groups G1 and G2, it notifies the members of the group G1 whether or not they can participate in the event. If there are no non-participating members, the members of group G1 repair the roof of client 101's home. On the other hand, if there is a non-participant, the shape of the skill information 111 is reduced depending on the skills and experience values of the non-participant, and the required skill information 110 is no longer satisfied.

In this case, the server 100 searches the user DB for a user 102 who satisfies the skills and experience values of the non-participant, and similarly notifies the user 102 of whether or not the user can participate. If the user 102 is able to participate, the reduced skill information 111 will satisfy the required skill information 110 based on the user's 102 skills and experience values. As a result, participating members belonging to group G1 and participating users outside group G1 repair the roof of client 101's home. On the other hand, if there is no user 102 who satisfies the skills and experience values of non-participants, or if the user 102 refuses to participate, the server 100 executes the same process for group G2 as for group G1.

<System configuration example>
FIG. 2 is an explanatory diagram showing an example of the system configuration of the matching system. Matching system 200 includes a server 100 and a terminal 201. The server 100 and the terminal 201 are communicably connected via a network 202 such as the Internet, a LAN (Local Area Network), or a WAN (Wide Area Network). The terminals 201 are also communicably connected via the network 202.

Server 100 is a computer that can access user DB 211, skill DB 212, and learning DB 213. The user DB 211, the skill DB 212, and the learning DB 213 may be stored in the server 100, or may be stored in another computer accessible from the server 100 via the network 202. Terminal 201 is a computer used by client 101 and user 102.

The user DB 211 is a database that stores information regarding the user 102 (user information). The user DB 211 will be described later with reference to FIG. 4. The skill DB 212 is a database that stores information regarding skills for each user. The skill DB 212 will be described later with reference to FIG. The learning DB 213 stores information necessary for generating a learning model by machine learning (including deep learning such as CNN (Convolutional Neural Network) and RNN (Recurrent Neural Network)) and making predictions using the learning model, such as training data sets and learning parameters. This is a database that stores information. The training data set is a combination of training data and ground truth data. Various such combinations exist.

For example, when generating a learning model that predicts the degree of existence of a house, the training data that makes up the training data set is, for example, image data of the house, and the correct data is the degree of damage (totally destroyed, large scale partially destroyed). , half destroyed, partially damaged, or undamaged).

When generating a learning model that generates a question from a request from the requester 101, the training data that constitutes the training data set is, for example, a request for an event that occurred in the past, and the correct answer data is for the request. These are past questions asked.

In addition, when generating a learning model that generates the required skill information 110 from the request or response content of the requester 101, the training data that constitutes the training data set may be, for example, a request for an event that occurred in the past or a request for the request. This is an answer to a past question posed to the user, and the correct answer data is the skill or detailed skill requested in the past and its requested experience value. A detailed skill is a skill obtained by subdividing a skill (described later in FIG. 5). Note that the generation of these learning models may be executed by the server 100, or a learning model learned by another computer or learning parameters constituting the learning model may be acquired from the other computer.

<Example of computer hardware configuration>
FIG. 3 is a block diagram showing an example of the hardware configuration of a computer (server 100, terminal 201). The computer 300 includes a processor 301, a storage device 302, an input device 303, an output device 304, and a communication interface (communication IF) 305. The processor 301, storage device 302, input device 303, output device 304, and communication IF 305 are connected by a bus 306. Processor 301 controls computer 300. The storage device 302 becomes a work area for the processor 301. Furthermore, the storage device 302 is a non-temporary or temporary recording medium that stores various programs and data. Examples of the storage device 302 include ROM (Read Only Memory), RAM (Random Access Memory), HDD (Hard Disk Drive), and flash memory. Input device 303 inputs data. Examples of the input device 303 include a keyboard, mouse, touch panel, numeric keypad, and scanner. Output device 304 outputs data. Examples of the output device 304 include a display, a printer, and a speaker. Communication IF 305 connects to network 202 and transmits and receives data.

<DB>
FIG. 4 is an explanatory diagram showing an example of the storage contents of the user DB 211. User DB 211 is a database that stores user information. The user DB 211 has fields such as user ID 401, user name 402, date of birth 403, gender 404, address 405, affiliated organization 406, affiliated community 407, friend ID 408, response rate 409, and participation. It has a rate of 410. The values of each field 401 to 409 on the same line constitute an entry indicating one user's information.

The user ID 401 is identification information that uniquely identifies the user 102. The user name 402 is the name of the user 102. The date of birth 403 is the date on which the user was born. The age of the user 102 can be calculated from the date of birth 403 and the current date and time. Gender 404 is information indicating whether the user 102 is male or female. Address 405 is the location of the residence where user 102 resides. The affiliated organization 406 is an organization to which the user 102 belongs. Belonging community 407 is a community to which the user 102 belongs. The friend ID 408 is the user ID 401 of the friend of the user 102.

The response rate 409 is the rate of responses to the event participation notification from the client 101. The denominator of the response rate 409 is the number of participation notifications. The numerator of response rate 409 is the total number of participation and non-participation. The participation rate 410 is the participation rate with respect to the event participation notification from the requester 101. The denominator of the participation rate 410 is the number of participation notifications. The numerator of participation rate 410 is the total number of participations. Note that the requester 101 shown in FIG. 1 may be the user 102 registered in the user DB 211, or may be an unregistered person.

FIG. 5 is an explanatory diagram showing an example of the storage contents of the skill DB 212. The skill DB 212 is a database that stores user skill information 500 for each user whose user information is registered in the user DB 211. The user skill information 500 is information indicating the skill of the user 102 and its experience value. Specifically, for example, the user skill information 500 includes a skill 501, a detailed skill 502, and a detailed experience value 503 as fields.

The skill 501 is a skill that the user 102 can learn. In this example, there are 10 types of skills shown in FIG. 1 (physical ability, general life, medicine/pharmaceutical science, agriculture, civil engineering and architecture, mechanical engineering, electrical engineering, information engineering, language ability, and law). The detailed skill 502 is a skill obtained by subdividing the skill 501. The detailed experience value 503 indicates the degree of acquisition of the detailed skill 502.

<Matching sequence>
FIG. 6 is a sequence diagram showing an example of a matching sequence by the matching system 200. The server 100 receives an event request such as "repair the roof of your home" from the terminal 201 of the client 101 (T601).

FIG. 7 is an explanatory diagram showing an example of a request input screen 700. The request input screen 700 is displayed on the terminal 201 of the requester 101 by accessing the server 100. The request input screen 700 includes a request input field 701 and a send button 702. When the send button 702 is pressed, the character string "The roof of my house was damaged due to a typhoon. I would like you to repair it" entered in the request input field 701 is sent to the server 100 as an event request (T601). .

Returning to FIG. 6, upon receiving the event request (T601), the server 100 executes question generation processing (step S601). The question generation process (step S601) is a process of outputting a question by inputting an event request to a learning model that generates a question from an event request.

Note that instead of executing the question generation process (step S601), the server 100 transfers the event request to the terminal 201 of the user 102 (T611), receives the question from the destination terminal 201 (T612) , is transferred to the terminal 201 of the client 101 (T602). Further, the server 100 may register the event request acquired in this way as training data and the question text as correct answer data in the learning data set of the learning DB 213. When the terminal 201 of the client 101 receives the question from the server 100, it displays an answer input screen.

FIG. 8 is an explanatory diagram showing an example of the answer input screen 800. The response input screen 800 displays the request input by the requester 101. The answer input screen 800 also includes question texts (in this example, Q1 to Q7) from the server 100, response input fields 801 to 807, and a send button 808. When the send button 808 is pressed, the screen returns to FIG. 6, and the character strings input in the answer input fields 801 to 807 are sent to the server 100 as an answer text (image data may be input in the answer input field 804). (T603).

When the server 100 receives the reply from the terminal 201 of the requester 101, it executes the requested skill information generation process (step S602). The required skill information generation process (step S602) is a process of outputting the required skill information 110 by inputting the received answer into the learning model that generates the required skill information 110. The server 100 transmits the requested skill information 110 generated by the requested skill information generation process (step S602) to the terminal 201 of the client 101 (T604).

FIG. 9 is an explanatory diagram showing an example of the required skill information display screen 900. The requested skill information display screen 900 is displayed on the terminal 201 of the client 101. The required skill information display screen 900 displays a required skill chart 901 and required detailed skill information 902 as the required skill information 110. A required skill chart 901 is a radar chart showing required experience values required of a group corresponding to an event for each of 10 types of required skills required for an event.

The requested detailed skill information 902 is information indicating the requested detailed skill 921 and the requested detailed experience value 922 required for the group corresponding to the event. When a required skill in the required skill chart 901 is pointed at with a cursor 903, detailed required skill information 902 regarding that skill 501 is displayed. In FIG. 9, since the cursor 903 is pointing to the requested skill "civil engineering and architecture," detailed requested skill information 902 regarding civil engineering and architecture is displayed.

The requested detailed skill 921 is not necessarily all the detailed skills 502 that constitute the skill 501, but is a specific detailed skill 502 obtained by inputting the received answer text into the learning model that generates the requested skill information 110. . For example, if the received response text is specific to roof repair, the required detail skills 921 for civil engineering and construction will also become specific detailed skills 502 specialized for roof repair, and Detailed skill 502 cannot be obtained. Therefore, the required experience value of the required skill in the required skill chart 901 is the sum of the required detailed experience value 922 of the specific required detailed skill 921 for civil engineering and construction specialized in roof repair.

Returning to FIG. 6, after transmitting the requested skill information 110 (T604), the server executes skill information generation processing (step S603). The skill information generation process (step S603) is a process of generating skill information based on the requested detailed skills 921 for each group. Specifically, for example, the server 100 limits the detailed skills 502 constituting the skill 501 to a specific requested detailed skill 921 for each skill 501 in each group, and limits the specific requested detailed skills 921 to each affiliated member. The detailed experience value 503 of the same detailed skill 502 is extracted from the skill DB 212.

The server 100 totals the detailed experience value 503 for each skill 501 of each affiliated member, and calculates the experience value for each skill 501 of the affiliated member. The server 100 calculates the experience value for each skill 501 in the satisfaction group by calculating the statistical value (maximum value, average value, median value, etc.) of the experience value of the affiliated members for each skill 501. In this way, the server 100 generates skill information based on the requested detailed skills 921 for each group.

Next, the server 100 executes group extraction processing (step S604). The group extraction process (step S604) is a process of extracting a group (organization or community) that satisfies the required skill information 110 from the user DB 211. Details of the group extraction process (step S604) will be described later.

FIG. 10 is an explanatory diagram showing the extraction results of the group extraction process (step S604). FIG. 10 shows an extraction result 1000 for group G1 as an example. The extraction result 1000 includes user information of the user 102 belonging to the group G1 and skill information 111 of the group G1. The skill information 111 of the group G1 includes a skill chart 1001 showing the group's experience value for each skill 501. Since the skill chart 1001 includes the required skill chart 901, the skill information 111 of group G1 satisfies the required skill information 110.

Returning to FIG. 6, the server 100 transmits a participation request to the terminal 201 of the member of the extraction group based on the extraction result 1000 obtained by the group extraction process (step S604) (T605).

FIG. 11 is an explanatory diagram showing an example of a participation request screen 1100. The participation request screen 1100 is displayed on the terminal 201 of the user 102 belonging to the extraction group. The participation request screen 1100 includes a participation permission selection area 1101, a requester information display area 1102, a request content display area 1103, and a participation candidate member display area 1104.

The participation selection area 1101 is an area for selecting whether to participate in the event, and includes a participation button 1111 and a non-participation button 1112. When the participation button 1111 is pressed, the user ID 401 and a reply to the effect of participating are sent to the server 100, and when the non-participation button 1112 is pressed, the user ID 401 and the reply to the effect of not participating are sent to the server 100. . The answer results are sent to the terminals 201 of other members of the extraction group.

In the client information display area 1102, information regarding the client 101 and a character string of the request are displayed. In the request content display area 1103, the request content of the requester 101 is displayed. For example, answer information 1131 and image data 1132 obtained at T603 are displayed. The participating member candidate display area 1104 displays user information of participating member candidates. Furthermore, in the user information of participating member candidates who have already sent their responses to the server 100, response information 1141 indicating participation and response information 1142 indicating non-participation are displayed. The response information 1141 and 1142 are displayed by receiving the response results of other affiliated members from the server 100.

Returning to FIG. 6, the terminal 201 of the member belonging to the extraction group transmits the answer to the server 100 by pressing the participation button 1111 or the non-participation button 1112 (T606). The server 100 executes participating member determination processing based on the answers (step S605). Participating member determination processing (step S605) is a process of determining participants who will participate in the event from among participating member candidates belonging to the extraction group. The server 100 removes the skills 501 (including detailed skills 502) and their experience values of the members who did not participate or did not respond from the group's skill information, and updates the group's skill information. Details of the participating member determination process (step S605) will be described later.

If the skill information of the group updated by the participating member determination process (step S605) satisfies the required skill information 110, the server 100 transmits a response to the event request to the terminal 201 of the client 101 (T607).

FIG. 12 is an explanatory diagram showing an example of the answer screen 1200. The response screen 1200 is displayed on the terminal 201 of the requester 101 that has received the response to the event request. The answer screen 1200 has an extraction group display area 1201, a participating member display area 1202, an OK button 1203, and a cancel button 1204. The extraction group display area 1201 is an area that displays the group name of the extraction group. Participating member display area 1202 is an area that displays user information of participating members. The OK button 1203 is a button for accepting an extraction group, and the cancel button 1204 is a button for rejecting an extraction group.

When the OK button 1203 is pressed, information indicating that the extraction group is accepted is sent to the server 100 (T608), and the extraction group's participation in the event is confirmed. When the cancel button 1204 is pressed, information to the effect that the extracted group is not accepted is transmitted to the server 100 (T608), confirming that the extracted group cannot participate in the event. In this way, the matching sequence ends.

<Group extraction process (step S604)>
FIG. 13 is a flowchart showing a detailed processing procedure example of the group extraction process (step S604) shown in FIG.

Next, the server 100 determines whether there is a group in which all the skills in the generated skill information satisfy the required experience value (step S1301). If there is one or more groups in which all skills in the generated skill information satisfy the required experience value (step S1301: Yes), the server 100 extracts the group as a satisfying group candidate (step S1302).

Next, the server 100 determines one sufficiency group from the extracted sufficiency group candidates based on predetermined conditions (step S1303). The predetermined conditions include, for example, conditions (1) to (5) below. Note that the combinations of conditions (1) to (5) are set in advance.

(1) The total experience value of all skills must be the maximum.
(2) The total difference between the experience value of each skill 501 and the required experience value is the minimum.
(3) Recalculate skill information by excluding members who are more than a predetermined distance away from the event location, and ensure that all skills in the recalculated skill information satisfy the required experience value.
(4) Recalculate skill information by excluding members whose response rate 409 is less than a predetermined response rate, and ensure that all skills in the recalculated skill information satisfy the required experience value.
(5) Recalculate skill information by excluding members whose participation rate 410 is less than a predetermined participation rate, and ensure that all skills in the recalculated skill information satisfy the required experience value.

By employing condition (1), satisficing group candidates that sufficiently satisfy the required skills are determined to be satisfiable groups. By employing condition (2), satisficing group candidates that meet the required skills are determined to be satisfiable groups. Conditions (3) to (5) are conditions that can be added to condition (1) or (2). By adopting condition (3), a satisfying group candidate having members who are geographically able to participate is determined as a satisfying group. By employing condition (4), a satisfying group candidate having members from whom answers are likely to be obtained is determined as a satisfying group. By adopting condition (5), a satisfying group candidate having members who are likely to participate is determined as a satisfying group.

Next, the server 100 transmits a participation request to the terminals 201 of the members of the satisfaction group (step S1304). On the other hand, in step S1302, if there is no group in which all the skills in the generated skill information satisfy the required experience value (step S1301: No), the server 100 sends a message to the client 101's terminal 201 indicating that it is not available. A notification is sent (step S1305). This ends the group extraction process (step S604).

After the group extraction process (step S604), in step S1305, a participation request is sent from the server 100 to the terminal 201 of the member belonging to the satisfaction group (T605), and an answer of participation or non-participation is sent from the terminal 201 of the member belonging to the satisfaction group. It is transmitted to the server 100 (T606).

<Participating member determination process (step S605)>
FIG. 14 is a flowchart showing a detailed example of the processing procedure of the participating member determination process (step S605) shown in FIG. First, the server 100 determines whether a sufficiency group exists (step S1401). If there is no sufficient group (step S1401: No), the server 100 ends the participating member determination process (step S605). In this case, the server 100 will send a reply to the terminal 201 of the requester 101 indicating that the corresponding group does not exist.

On the other hand, if a satisfied group exists (step S1404: Yes), the server 100 waits for a response until a predetermined time has elapsed (step S1402: No). If the predetermined time has elapsed (step S1402: No), the server 100 acquires the experience points of the members (participating members) of the satisfied group who answered that they will participate, for each skill 501, and uses the same calculation method as in step S1301 to calculate the experience value of the satisfied group. The skill information of the group is updated (step S1403).

Next, the server 100 determines whether all skills satisfy the required experience value for the updated skill information (step S1404). If satisfied (step S1404: Yes), the server 100 transmits response information including the group name and participating members of the satisfied group to the terminal 201 of the requester 101 (step S1405). As a result, the participation request screen 1100 shown in FIG. 11 is displayed on the terminal 201 of the requester 101.

On the other hand, if all the skills do not satisfy the required experience value for the updated skill information (step S1404: No), the server 100 executes the missing skill replenishment process (step S1406). The missing skill replenishment process (step S1406) is a process of replenishing the experience value of the skill 501 that does not satisfy the required experience value in the updated skill information using another user 102.

FIG. 15 is an explanatory diagram showing an example of determining whether or not the required experience value can be satisfied in step S1404. When there is a non-participating member in group G1, the skill chart 1501 of the updated skill information 1500 is smaller than the original skill chart 1001 due to the skill 501 possessed by the non-participating member and its experience value. There are also skills such as electrical engineering and civil engineering architecture that do not satisfy the required experience value of the required skill chart 901. Therefore, all the skills in the updated skill information do not satisfy the required experience value (step S1404: No), and the process moves to the insufficient skill replenishment process (step S1406).

<Insufficient skill replenishment process (step S1406)>
FIG. 16 is a flowchart illustrating a detailed processing procedure example of the missing skill replenishment process (step S1406). The server 100 identifies the skill 501 that does not satisfy the required experience value with respect to the updated skill information (step S1601). For example, in the example of FIG. 15, server 100 specifies physical ability, law, electrical engineering, and civil engineering.

Next, the server 100 searches for a user who has an experience value that satisfies the required experience value for the skill 501 that does not satisfy the required experience value (step S1602). Specifically, for example, the server 100 searches the user DB 211 for a user whose experience value is greater than or equal to the experience value of the non-participating user 102 for the skill 501 that does not satisfy the required experience value. Note that the search target in step S1602 will be described later with reference to FIG.

If the corresponding user 102 exists (step S1603: Yes), the server 100 transmits a participation request to the terminal 201 of the corresponding user 102 (step S1604), and proceeds to step S1402. As a result, the participation request screen 1100 shown in FIG. 11 is displayed on the terminal 201 of the corresponding user 102.

On the other hand, if there is no corresponding user 102 in step S1603 (step S1603: No), the server 100 determines whether there is an unselected satisfying group candidate extracted in step S1303 (step S1605). If there are unselected sufficiency group candidates (step S1605: Yes), the process moves to step S1304. On the other hand, if there are no unselected satisfactory group candidates (step S1605: No), the server 100 ends the missing skill replenishment process (step S605).

FIG. 17 is an explanatory diagram showing an example of a user search in step S1602. In FIG. 17, Kenta Kobayashi, Hanako Kodaira, and Kenichi Baba are participating members 1701 of group G1, and Kota Shimizu, Aiko Sato, Tsuyoshi Watanabe, and Minoru Matsuki are supplementary members 1702 who have been supplemented by the missing skill supplement process (step S1406). It is.

The skill chart 1501 of the updated skill information 1500 is smaller than the original skill chart 1001 (see FIG. 10), and for example, the required experience value of the required skill chart 901 for physical ability, law, electrical engineering, civil engineering, etc. They also have unsatisfied skills. For example, regarding law, Aiko Sato, who belongs to the same organization (data company) as Hanako Kodaira, one of the participating members 1701, is searched as a candidate for supplementary member 1702. Regarding electrical engineering, Kota Shimizu, a friend of Kenta Kobayashi, one of the participating members 1701, is searched as a candidate for supplementary member 1702. Kota Shimizu is a friend of Kenta Kobayashi, and their user IDs 401 are registered in the friend IDs of the user DB 211. In this way, in step S1602, by searching for users who are connected to participating members, it is possible to improve the participation rate 410 of supplementary members 1702.

Regarding physical ability, Kenichi Baba, one of the participating members 1701, and Tsuyoshi Watanabe, who has no direct connection with organizations, communities, or friends, and regarding civil engineering and architecture, Minoru Matsuki, who has no connection with Kenichi Baba in the national government, Searched as a candidate for supplementary member 1702. Specifically, for example, if one or more users 1703 are present between the participating members 1701 and 1701, they are searched as candidates with no direct connection. The number of intervening users 1703 can be set on the server 100. The more people there are, the lower the probability that they will become acquainted. In this way, in step S1602, users who are connected to the participating members 1701 through connections equal to or more than the number of intervening members are searched for as candidates for supplementary members 1702, and users 102 who have no opportunity to get to know each other can interact with each other. can support.

Further, the server 100 may search for users who reside at an address 405 within a predetermined distance from the house that is the event site 1704, such as Minoru Matsuki. In this way, by searching for users who are familiar with the surroundings of the site as candidates for supplementary members 1702, work efficiency can be improved.

Furthermore, the server 100 may include users with whom there is no direct connection as search targets based on the age of the user 102 and the average age of the participating members of the group G1. For example, if you want the wisdom of a person with seniority, you can choose a user who is older than the average age of the participating members of group G1, for example, a user who is N years (N is an integer greater than or equal to 1) older than the average age, or a user who is 50 years older than the average age. The search target may be users who are over a predetermined age, such as those over a certain age. In addition, users who are younger than the average age of the participating members of group G1, such as users who are N years (N is an integer greater than or equal to 1) younger than the average age, or users who are 25 years or younger, are searched for. Good too. This makes it possible to supplement the participating members of group G1, which are biased toward the same generation, with members of different generations.

Further, the server 100 may search for users who are equivalent to the average age of the participating members of the group G1 (for example, from M years younger to M years older than the average age). This makes it possible to supplement with members of the same generation.

<Post-processing>
FIG. 18 is a flowchart illustrating a detailed processing procedure example of post-processing. Post-processing is processing after the event ends. The server 100 waits for the event implementation date to pass (step S1801: No), and when the event implementation date has passed, updates the response rate 409 and participation rate 410 for each of the members belonging to the fulfillment group and the supplementary member candidates (step S1801: No). S1802). Next, the server 100 updates the experience value for each of the participating members and supplementary members of the satisfaction group (step S1802).

The amount of updated experience points may be based on the self-reports of the participating members 1701 and supplementary members 1702, or may be based on reports from other participating members 1701 and other supplementary members 1702, or may be based on reports from the requester 101. May be based on Then, the server 100 transmits the update result to the terminal 201 of the user 102 that has been updated in steps S1802 and S1803 (step S1804). As a result, an update result screen is displayed on the terminal 201 of the user 102.

FIG. 19 is an explanatory diagram showing an example of an update result screen 1900. The update result screen 1900 displays the response rate 409, participation rate 410, and experience value for each skill as the update results in steps S1802 and S1803.

In the example described above, the server 100 executed the missing skill replenishment process (step S1406) without cooperating with the terminal 201 of the client 101. However, as described below, the server 100 may cooperate with the terminal 201 of the client 101 to execute the missing skill replenishment process (step S1406). Specifically, for example, when the server 100 searches for supplementary member candidates in step S1602, it transmits the search results to the terminal 201 of the client 101.

FIG. 20 is an explanatory diagram showing an example of a supplementary member selection screen 2000. The supplementary member selection screen 2000 includes a skill information display area 2001, a detailed skill information display area 2002, and a supplementary member candidate list display area 2003. The skill information display area 2001 is an area for displaying the skill chart 1501 of the updated skill information 1500. A required skill chart 901 is also superimposed on the updated skill information 1500.

The detailed skill information display area 2002 is an area that displays detailed skill information 2020 of the skill selected with the cursor 2010 in the updated skill information 1500. Detailed skill information 2020 is information in which detailed skills 502 and their detailed experience values 503 are associated with each other. In FIG. 20, since electrical engineering has been selected with the cursor 2010, detailed skill information 2020 regarding electrical engineering is displayed in the detailed skill information display area 2002.

The supplementary member candidate list display area 2003 is an area that displays a list of supplementary member candidates. A check box 2030 is provided for each supplementary member candidate, and when the requester 101 operates the terminal 201 and enters a check in the checkbox 2030, the experience value of the skill 501 of that supplementary member candidate is reflected in the skill chart 1501. be done.

FIG. 21 is an explanatory diagram showing an example of the supplementary member selection screen when the check box 2030 is input. FIG. 21 shows a state in which a check has been entered in the check box 2030 for Kota Shimizu. In this case, the experience value of Kota Shimizu's skill 501 is reflected in the skill chart 1501, updated in the skill chart 2100, and detailed skill information 2020 is also updated. Thereby, the requester 101 can visually confirm which supplementary member candidate should be added and the experience value of which skill 501 will satisfy the required experience value.

After this, when the OK button 2005 is pressed, the result of checking the check box 2030 is transmitted to the server 100. The server 100 transmits a participation request to the terminal 201 of the supplementary member candidate whose check box 2030 is checked (step S1604). Note that if the requested experience value is not satisfied with the supplementary member candidates for which the check has been input, the server 100 may transmit the search results again to the terminal 201 of the requester 101 and display the supplementary member selection screen 2000. Furthermore, for skills that do not satisfy the required experience value, the server 100 may check whether the corresponding user 102 exists without inquiring the terminal 201 of the client 101 again (step S1604). In this way, the client 101 can check the supplementary members and decide whether to have them participate in the event.

In this way, according to the matching system 200 described above, it is possible to respond to the requests of the clients 101 who are in trouble due to disasters or rural-urban disparities.

Note that the present invention is not limited to the embodiments described above, and includes various modifications and equivalent configurations within the scope of the appended claims. For example, the embodiments described above have been described in detail to explain the present invention in an easy-to-understand manner, and the present invention is not necessarily limited to having all the configurations described. Further, a part of the configuration of one embodiment may be replaced with the configuration of another embodiment. Further, the configuration of one embodiment may be added to the configuration of another embodiment. Furthermore, other configurations may be added to, deleted from, or replaced with some of the configurations of each embodiment.

Further, each of the above-mentioned configurations, functions, processing units, processing means, etc. may be realized in part or in whole by hardware, for example by designing an integrated circuit, and a processor realizes each function. It may also be realized by software by interpreting and executing a program.

Information such as programs, tables, and files that realize each function is stored in storage devices such as memory, hard disks, and SSDs (Solid State Drives), or on IC (Integrated Circuit) cards, SD cards, and DVDs (Digital Versatile Discs). It can be stored on a medium.

Furthermore, the control lines and information lines shown are those considered necessary for explanation, and do not necessarily show all the control lines and information lines necessary for implementation. In reality, almost all configurations can be considered interconnected.

Claims (11)

An extraction device comprising a processor that executes a program, a storage device that stores the program, and a communication interface that can communicate with a plurality of terminals,
Each user of the terminal can access a database that stores skills possessed by the user, experience points indicating the degree of acquisition of the skill, and a group to which the user belongs;
The processor includes:
a first communication process of receiving an event request requesting the event from a terminal of an event requester and transmitting it to each of the terminals;
After the first communication process, a second communication process of receiving a question regarding the event from each of the terminals, and transmitting the question to the requester's terminal;
After the second communication process, receiving an answer to the question from the client's terminal, and inputting the answer into a learning model that outputs experience points required for each skill when answer information is input. Accordingly, required skill information indicating the experience value required for the event for each skill is generated, and for each group, a statistical value of the experience value of each skill of the user in the group in the required skill information is calculated. a generation process of generating skill information for each group ;
an extraction process for extracting a specific group that satisfies the requested skill information from among the skill information for each group generated by the generation process;
As a result of sending a request to participate in the event to the terminal of a specific user belonging to the specific group extracted by the extraction process, based on the response from the terminal of the specific user, the specific information that the specific group has An update process that updates the skill information of
a determination process of determining whether the specific skill information updated by the update process satisfies the required skill information;
a transmission process of transmitting the determination result of the determination process to the client 's terminal;
An extraction device characterized by performing the following. The extraction device according to claim 1,
The database stores an address for each user,
In the extraction process, the processor excludes users whose distance between the event location and the address is a predetermined distance or more from among the specific users, and determines the group to which the remaining specific users belong. Extract as a group,
An extraction device characterized by: The extraction device according to claim 1,
The database stores, for each user, a response rate indicating the percentage of responses to requests to participate in past events;
In the extraction process, the processor excludes users whose response rate is below a threshold value from among the specific users, and extracts a group to which the remaining specific users belong as the specific group.
An extraction device characterized by: The extraction device according to claim 1,
The database stores, for each user, a participation rate indicating a participation rate with respect to requests for participation in past events;
In the extraction process, the processor excludes users whose participation rate is below a threshold value from among the specific users, and extracts a group to which the remaining specific users belong as the specific group.
An extraction device characterized by: The extraction device according to claim 1,
In the update process, the processor updates the specific skill information based on the skills and experience values of the specific user who has responded indicating participation in the event.
An extraction device characterized by: The extraction device according to claim 1,
The processor includes:
If it is determined by the determination process that the specific skill information after the update does not satisfy the required skill information, the person has the skill that is no longer satisfied and the required experience value necessary for the skill that is no longer satisfied is satisfied. executing a search process to search the database for other users outside the specific group;
In the update process, the processor updates the specific skill information based on a response from the other user's terminal as a result of transmitting a request to participate in the event to the other user's terminal.
An extraction device characterized by: The extraction device according to claim 6,
In the update process, the processor updates the specific skill information based on the skills and experience values of the other users who have responded indicating participation in the event.
An extraction device characterized by: The extraction device according to claim 6,
In the search process, the processor searches for a user who belongs to another group to which the specific user belongs as the other user.
An extraction device characterized by: The extraction device according to claim 6,
In the search process, the processor searches for a user who belongs to another group to which the specific user does not belong, as the other user.
An extraction device characterized by: The extraction device according to claim 9,
The database stores an address for each user,
In the search process, the processor searches for a user who belongs to another group to which the specific user does not belong and who has an address within a predetermined distance from the event site as the other user.
An extraction device characterized by: An extraction method executed by an extraction device having a processor that executes a program, a storage device that stores the program, and a communication interface that can communicate with a plurality of terminals,
The extraction device is capable of accessing a database that stores, for each user of the terminal, skills possessed by the user, experience values indicating the degree of acquisition of the skill, and a group to which the user belongs,
The extraction method is
The processor,
a first communication process of receiving an event request requesting the event from a terminal of an event requester and transmitting it to each of the terminals;
After the first communication process, a second communication process of receiving a question regarding the event from each of the terminals, and transmitting the question to the requester's terminal;
After the second communication process, receiving an answer to the question from the client's terminal, and inputting the answer into a learning model that outputs experience points required for each skill when answer information is input. Accordingly, required skill information indicating the experience value required for the event for each skill is generated, and for each group, a statistical value of the experience value of each skill of the user in the group in the required skill information is calculated. a generation process of generating skill information for each group ;
an extraction process for extracting a specific group that satisfies the requested skill information from among the skill information for each group generated by the generation process;
As a result of sending a request to participate in the event to the terminal of a specific user belonging to the specific group extracted by the extraction process, based on the response from the terminal of the specific user, the specific information that the specific group has An update process that updates the skill information of
a determination process of determining whether the specific skill information updated by the update process satisfies the required skill information;
a transmission process of transmitting the determination result of the determination process to the client 's terminal;
An extraction method characterized by performing.

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